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Light interception modelling using unstructured LiDAR data in avocado orchards
Univ Sydney, Australia.
Univ Sydney, Australia.
Linköping University.
2018 (English)In: Computers and Electronics in Agriculture, ISSN 0168-1699, E-ISSN 1872-7107, Vol. 153, p. 177-187Article in journal (Refereed) Published
Abstract [en]

In commercial fruit farming, managing the light distribution through canopies is important because the amount and distribution of solar energy that is harvested by each tree impacts the production of fruit quantity and quality. It is therefore an important characteristic to measure and ultimately to control with pruning. We present a solar-geometric model to estimate light interception in individual avocado (Persea americana Mill.) trees, that is designed to scale to whole-orchard scanning, ultimately to inform pruning decisions. The geometry of individual trees was measured using handheld mobile LiDAR and represented by point clouds. A discrete energy distribution model of the hemispherical sky was synthesised using public weather records. The light from each sky node was then ray traced, applying a radiation absorption model where rays pass the point cloud representation of the tree. The model was validated using ceptometer energy measurements at the canopy floor, and model parameters were optimised by analysing the error between modelled and measured energies. The model was shown to perform well qualitatively through visual comparison with tree shadows in photographs, and quantitatively well with R-2 = 0.854, suggesting it is suitable to use in the context of agricultural decision support systems, in future work.

Place, publisher, year, edition, pages
ELSEVIER SCI LTD , 2018. Vol. 153, p. 177-187
Keywords [en]
Agriculture; Lidar; Light interception; Orchard; Phenotyping; Pruning
National Category
Ecology
Identifiers
URN: urn:nbn:se:liu:diva-152062DOI: 10.1016/j.compag.2018.08.020ISI: 000446284900017OAI: oai:DiVA.org:liu-152062DiVA, id: diva2:1259510
Note

Funding Agencies|Australian Centre for Field Robotics (ACFR) at The University of Sydney; Australian Government Department of Agriculture and Water Resources

Available from: 2018-10-30 Created: 2018-10-30 Last updated: 2018-10-30

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CiteExportLink to record
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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf